%matplotlib inline
import pandas as pd
import matplotlib.pyplot as plt

raw_data = {'first_name': ['Jason', 'Molly', 'Tina', 'Jake', 'Amy'],
        'pre_score': [4, 24, 31, 2, 3],
        'mid_score': [25, 94, 57, 62, 70],
        'post_score': [5, 43, 23, 23, 51]}

df = pd.DataFrame(raw_data, columns = ['first_name', 'pre_score', 'mid_score', 'post_score'])
df

/* Create a figure with a single subplot */
f, ax = plt.subplots(1, figsize=(10,5))

/* Set bar width at 1 */
bar_width = 1

/* positions of the left bar-boundaries */
bar_l = [i for i in range(len(df['pre_score']))] 

/* positions of the x-axis ticks (center of the bars as bar labels) */
tick_pos = [i+(bar_width/2) for i in bar_l] 

/* Create the total score for each participant */
totals = [i+j+k for i,j,k in zip(df['pre_score'], df['mid_score'], df['post_score'])]

/* Create the percentage of the total score the pre_score value for each participant was */
pre_rel = [i / j * 100 for  i,j in zip(df['pre_score'], totals)]

/* Create the percentage of the total score the mid_score value for each participant was */
mid_rel = [i / j * 100 for  i,j in zip(df['mid_score'], totals)]

/* Create the percentage of the total score the post_score value for each participant was */
post_rel = [i / j * 100 for  i,j in zip(df['post_score'], totals)]

/* Create a bar chart in position bar_1 */
ax.bar(bar_l, 
       pre_rel, 
       label='Pre Score', 
       alpha=0.9, 
       color='019600',
       width=bar_width,
       edgecolor='white'
       )

/* Create a bar chart in position bar_1 */
ax.bar(bar_l, 
       mid_rel, 
       bottom=pre_rel, 
       label='Mid Score', 
       alpha=0.9, 
       color='3C5F5A', 
       width=bar_width,
       edgecolor='white'
       )

/* Create a bar chart in position bar_1 */
ax.bar(bar_l, 
       post_rel, 
       bottom=[i+j for i,j in zip(pre_rel, mid_rel)], 
       label='Post Score',
       alpha=0.9, 
       color='219AD8', 
       width=bar_width,
       edgecolor='white'
       )

/* Set the ticks to be first names */
plt.xticks(tick_pos, df['first_name'])
ax.set_ylabel("Percentage")
ax.set_xlabel("")

/* Let the borders of the graphic */
plt.xlim([min(tick_pos)-bar_width, max(tick_pos)+bar_width])
plt.ylim(-10, 110)

/* rotate axis labels */
plt.setp(plt.gca().get_xticklabels(), rotation=45, horizontalalignment='right')

/* shot plot */
plt.show()